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MeshCNN Fundamentals: Geometric Learning through a Reconstructable
  Representation

MeshCNN Fundamentals: Geometric Learning through a Reconstructable Representation

27 May 2021
Amir Barda
Yotam Erel
Amit H. Bermano
    3DV
ArXivPDFHTML

Papers citing "MeshCNN Fundamentals: Geometric Learning through a Reconstructable Representation"

4 / 4 papers shown
Title
Primal-Dual Mesh Convolutional Neural Networks
Primal-Dual Mesh Convolutional Neural Networks
Francesco Milano
Antonio Loquercio
Antoni Rosinol
Davide Scaramuzza
Luca Carlone
3DPC
AI4CE
53
89
0
23 Oct 2020
DensePoint: Learning Densely Contextual Representation for Efficient
  Point Cloud Processing
DensePoint: Learning Densely Contextual Representation for Efficient Point Cloud Processing
Yongcheng Liu
Bin Fan
Gaofeng Meng
Jiwen Lu
Shiming Xiang
Chunhong Pan
3DPC
119
270
0
09 Sep 2019
PointNet: Deep Learning on Point Sets for 3D Classification and
  Segmentation
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
C. Qi
Hao Su
Kaichun Mo
Leonidas J. Guibas
3DH
3DPC
3DV
PINN
222
14,103
0
02 Dec 2016
Geometric deep learning: going beyond Euclidean data
Geometric deep learning: going beyond Euclidean data
M. Bronstein
Joan Bruna
Yann LeCun
Arthur Szlam
P. Vandergheynst
GNN
253
3,239
0
24 Nov 2016
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